For IT Infrastructure Support (ITIS), it is crucial to identify opportunities for reducing service costs and improving service quality. We focus on streamlining service levels i.e., finding right resolution level for each ticket, to reduce time, efforts and cost for ticket handling, without affecting workloads and user satisfaction. We formalize this problem and present two statistics-based search algorithms for identifying problems suitable for left-shift (from expensive, expertise intensive L2 level to cheaper, simpler L1 level) and right-shift (from L1 to L2). The approach is domain-driven: it produces directly usable and often novel results, without any trial-and error experimentation, along with detailed justifications and predicted impacts. This helps in acceptance among end-users and more active use of the results. We discuss one real-life case-study of results produced by the algorithms.